Free Microsoft AI-102 Practice Test & Real Exam Questions
You are developing a streaming Speech to Text solution that will use the Speech SDK and MP3 encoding.
You need to develop a method to convert speech to text for streaming MP3 data.
How should you complete the code? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
You need to develop a method to convert speech to text for streaming MP3 data.
How should you complete the code? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Correct Answer:
Explanation:
Scenario Recap
You are building a streaming Speech-to-Text solution using the Speech SDK.
Input audio format: MP3 encoding
You must configure the audio stream format and the recognizer properly.
Code Analysis
Audio Format
For MP3 streams, the correct method is:
AudioStreamFormat.GetCompressedFormat(AudioStreamContainerFormat.MP3)
This creates an audio format object for compressed MP3 input.
Recognizer
Since the task is speech-to-text transcription, you need the SpeechRecognizer class.
Other options like KeywordRecognizer, SpeakerRecognizer, or SpeechSynthesizer are not appropriate (they handle keyword spotting, speaker identification, or text-to-speech).
Completed Code Snippet
var audioFormat = AudioStreamFormat.GetCompressedFormat(AudioStreamContainerFormat.MP3); var speechConfig = SpeechConfig.FromSubscription( " 18c51a87-3a69-47a8-aedc-a54745f708a1 " , " westus
" );
var audioConfig = AudioConfig.FromStreamInput(pushStream, audioFormat); using ( var recognizer = new SpeechRecognizer(speechConfig, audioConfig))
{
var result = await recognizer.RecognizeOnceAsync();
var text = result.Text;
}
Final Answer (Answer Area Selections)
AudioFormat: AudioStreamFormat.GetCompressedFormat
Recognizer: SpeechRecognizer
Microsoft References
Speech SDK - AudioStreamFormat
SpeechRecognizer class
You train an Azure Custom Vision object detection model to identify a company ' s products by using the Retail domain.
You plan to deploy the model as part of a mobile app for Android phones.
You need to prepare the model for deployment.
Which three actions should you perform in sequence? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order.
You plan to deploy the model as part of a mobile app for Android phones.
You need to prepare the model for deployment.
Which three actions should you perform in sequence? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order.
Correct Answer:
Explanation:
For deployment to a mobile app (Android), Custom Vision requires a compact domain so the model can be exported and run on-device (e.g., as TensorFlow Lite or ONNX). The model was trained using the Retail domain, which is not an exportable compact domain for object detection. Therefore:
Change the model domain to an exportable Object Detection (compact) domain (e.g., General [compact]).
Retrain the model so weights are learned under the new domain-domain changes require retraining.
Export the model for Android (typically TensorFlow Lite or ONNX) and integrate it into the app.
This sequence prepares the model for on-device mobile deployment with minimal extra development.
References (Microsoft Azure AI Solution)
Custom Vision: Only compact domains support model export for edge/mobile.
Changing a domain requires retraining the iteration.
Exporting object detection models supports TensorFlow/TensorFlow Lite/ONNX formats for Android integration.
You are designing a conversational interface for an app that will be used to make vacation requests. The interface must gather the following data:
* The start date of a vacation
* The end date of a vacation
* The amount of required paid time off
The solution must minimize dialog complexity. Which type of dialog should you use?
* The start date of a vacation
* The end date of a vacation
* The amount of required paid time off
The solution must minimize dialog complexity. Which type of dialog should you use?
Correct Answer: A
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You have an Azure subscription that contains an Azure Al Content Safety resource named Resource1 and a storage account named storage1.
You create a blob container named container1 and upload a sample set of image files to container1.
You need to validate whether Resource1 can identify images that contain potential violence.
How should you complete the cURL command? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
You create a blob container named container1 and upload a sample set of image files to container1.
You need to validate whether Resource1 can identify images that contain potential violence.
How should you complete the cURL command? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Correct Answer:
Explanation:
To validate that your Azure AI Content Safety resource can identify images containing potential violence, you must call the Image Analyze operation of Content Safety. The REST endpoint for this operation is:
POST {endpoint}/contentsafety/image:analyze?api-version=2024-09-01
This operation analyzes an image for the four harm categories Hate, SelfHarm, Sexual, and Violence.
Therefore, the correct base path is /contentsafety, and the correct operation is image analyze (shown in the hotspot as /imageanalyze).
Microsoft References
REST API: Analyze Image - POST {endpoint}/contentsafety/image:analyze?api-version=2024-09-01 ; categories include Hate, SelfHarm, Sexual, and Violence. Microsoft Learn Quickstart: Analyze image content with Azure AI Content Safety (overview and examples). Microsoft Learn Harm categories concept (lists Violence among supported categories). Microsoft Learn
You have the following data sources:
Finance: On-premises Microsoft SQL Server database
Sales: Azure Cosmos DB using the Core (SQL) API
Logs: Azure Table storage
HR: Azure SQL database
You need to ensure that you can search all the data by using the Azure Cognitive Search REST API. What should you do?
Finance: On-premises Microsoft SQL Server database
Sales: Azure Cosmos DB using the Core (SQL) API
Logs: Azure Table storage
HR: Azure SQL database
You need to ensure that you can search all the data by using the Azure Cognitive Search REST API. What should you do?
Correct Answer: B
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You are building a language learning solution.
You need to recommend which Azure services can be used to perform the following tasks:
* Analyze lesson plans submitted by teachers and extract key fields, such as lesson times and required texts.
* Analyze learning content and provide students with pictures that represent commonly used words or phrases in the text The solution must minimize development effort.
Which Azure service should you recommend for each task? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
You need to recommend which Azure services can be used to perform the following tasks:
* Analyze lesson plans submitted by teachers and extract key fields, such as lesson times and required texts.
* Analyze learning content and provide students with pictures that represent commonly used words or phrases in the text The solution must minimize development effort.
Which Azure service should you recommend for each task? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Correct Answer:
Explanation:
Analyze lesson plans and extract key fields
Use Azure AI Document Intelligence (Form Recognizer) to automatically extract structured data (dates/times, required texts, names, etc.) from uploaded lesson-plan documents (PDFs/images). It provides prebuilt and custom extraction with minimal code via Document Intelligence Studio.
Analyze learning content and show pictures for common words/phrases
Use Immersive Reader, which includes features like Picture Dictionary and text comprehension supports directly in apps with minimal development. It can highlight words and show illustrative images to aid vocabulary learning-exactly the requirement.
Other options are not a fit:
Azure AI Custom Vision is for training image classifiers/detectors, not text comprehension.
Azure AI Search indexes and searches content; it doesn't provide picture dictionary/reading experience.
Microsoft Azure AI References
Document Intelligence (Form Recognizer) overview & extraction capabilities: learn.microsoft.com/azure/ai- services/document-intelligence/overview Immersive Reader - Picture Dictionary & reading features: learn.microsoft.com/azure/ai-services/immersive- reader/overview
You have a library that contains thousands of images.
You need to tag the images as photographs, drawings, or clipart.
Which service endpoint and response property should you use? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
You need to tag the images as photographs, drawings, or clipart.
Which service endpoint and response property should you use? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Correct Answer:
Explanation:
Service endpoint # Computer Vision analyze images
Property # imageType
The task:
" You have a library with thousands of images. You need to tag the images as photographs, drawings, or clipart. " Which service endpoint?
Computer Vision analyze images # Provides a broad analysis including categories, tags, descriptions, and image type (photo, drawing, clipart). # Computer Vision object detection # Identifies objects (people, cars, animals), not image type.
Custom Vision image classification / object detection # Requires custom training, not needed since the built- in Computer Vision service already supports this.
Correct: Computer Vision analyze images
Which property?
categories # Provides predefined categories (e.g., outdoor, indoor, people), not specifically drawing/clipart
/photo.
description # Generates captions in natural language, not classification into photo/drawing/clipart.
imageType # Identifies if an image is a photograph, line drawing, or clipart. # metadata # Provides size, format, dimensions.
objects # Lists detected objects, not image type.
Correct: imageType
Service endpoint # Computer Vision analyze images
Property # imageType
Microsoft References
Computer Vision Analyze API
ImageType property in Computer Vision
You are developing a call to the Face API. The call must find similar faces from an existing list named employeefaces. The employeefaces list contains 60,000 images.
How should you complete the body of the HTTP request? To answer, drag the appropriate values to the correct targets. Each value may be used once, more than once, or not at all. You may need to drag the split bar between panes or scroll to view content.
NOTE: Each correct selection is worth one point.
How should you complete the body of the HTTP request? To answer, drag the appropriate values to the correct targets. Each value may be used once, more than once, or not at all. You may need to drag the split bar between panes or scroll to view content.
NOTE: Each correct selection is worth one point.
Correct Answer:
Explanation:
You are calling the Face API to find similar faces from an existing list called employeefaces.
Key facts from the scenario:
The list contains 60,000 images.
In Face API:
faceListId # limited to 1,000 faces.
largeFaceListId # designed for very large lists, up to 1,000,000 faces.
Since employeefaces has 60,000 images, you must use LargeFaceListId, not faceListId.
Parameters in the Request Body
" faceId " : " 18c51a87-3a69-47a8-aedc-a54745f708a1 "
This is the face to search for.
" largeFaceListId " : " employeefaces "
Must use LargeFaceListId because the list has 60,000 images.
" maxNumOfCandidatesReturned " : 1
Limits the number of matches returned.
" mode " : " matchFace "
Two options exist:
" matchFace " # returns the most similar individual faces.
" matchPerson " # groups faces by person.
Since the requirement is find similar faces, use " matchFace " .
Completed Answer
{
" faceId " : " 18c51a87-3a69-47a8-aedc-a54745f708a1 " ,
" largeFaceListId " : " employeefaces " ,
" maxNumOfCandidatesReturned " : 1 ,
" mode " : " matchFace "
}
Correct Values to Drag and Drop
LargeFaceListId # " employeefaces "
matchFace # " mode "
Final Answer:
First blank: LargeFaceListId
Second blank: matchFace
Microsoft References
Face API - Find Similar
Face API - Large Face List operations
You have an Azure subscription that contains a Microsoft Foundry hub named Hub1, an Azure OpenAI resource named resource1, and a user named User1.
You need to ensure that User1 can create a new Azure Content Understanding in Foundry Tools project in Hub1. The solution must follow the principle of least privilege.
Which role should you assign to User1?
You need to ensure that User1 can create a new Azure Content Understanding in Foundry Tools project in Hub1. The solution must follow the principle of least privilege.
Which role should you assign to User1?
Correct Answer: D
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Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution.
After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear in the review screen.
You build a language model by using a Language Understanding service. The language model is used to search for information on a contact list by using an intent named FindContact.
A conversational expert provides you with the following list of phrases to use for training.
Find contacts in London. Who do I know in Seattle?
Search for contacts in Ukraine.
You need to implement the phrase list in Language Understanding.
Solution: You create a new pattern in the FindContact intent.
Does this meet the goal?
After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear in the review screen.
You build a language model by using a Language Understanding service. The language model is used to search for information on a contact list by using an intent named FindContact.
A conversational expert provides you with the following list of phrases to use for training.
Find contacts in London. Who do I know in Seattle?
Search for contacts in Ukraine.
You need to implement the phrase list in Language Understanding.
Solution: You create a new pattern in the FindContact intent.
Does this meet the goal?
Correct Answer: A
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You plan to use containerized versions of the Anomaly Detector API on local devices for testing and in on- premises datacenters.
You need to ensure that the containerized deployments meet the following requirements:
Prevent billing and API information from being stored in the command-line histories of the devices that run the container.
Control access to the container images by using Azure role-based access control (Azure RBAC).
Which four actions should you perform in sequence? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order. (Choose four.) NOTE: More than one order of answer choices is correct. You will receive credit for any of the correct orders you select.
You need to ensure that the containerized deployments meet the following requirements:
Prevent billing and API information from being stored in the command-line histories of the devices that run the container.
Control access to the container images by using Azure role-based access control (Azure RBAC).
Which four actions should you perform in sequence? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order. (Choose four.) NOTE: More than one order of answer choices is correct. You will receive credit for any of the correct orders you select.
Correct Answer:
Explanation:
Comprehensive Detailed Explanation
You are deploying Anomaly Detector API as a container. The key requirements are:
Prevent billing and API keys from being exposed in command-line history.
Control access to container images using Azure RBAC.
Step-by-step reasoning:
Pull the Anomaly Detector container image
Microsoft Cognitive Services (including Anomaly Detector) provides container images via Microsoft Container Registry.
You must first pull the container image locally.
Push the image to an Azure container registry (ACR)
To enforce Azure RBAC, you need to use Azure Container Registry instead of Docker Hub.
Storing in ACR ensures authentication and role-based access control to the image.
Distribute a docker run script
Instead of providing credentials directly on the command line (which risks storing API keys in shell history), best practice is to distribute a docker run script (or use environment variables / mounted files) to run the container.
This prevents exposure of sensitive information.
Run the container on local devices or on-premises datacenters
The container now runs securely, with API key and billing info injected at runtime via environment variables or mounted secrets.
Incorrect Options
Create a custom Dockerfile # Not needed, because Microsoft provides the official Anomaly Detector container image.
Build the image # Not required; again, the container is prebuilt.
Push the image to Docker Hub # Does not allow RBAC, so this would not meet the security requirement.
Correct Sequence:
Pull the Anomaly Detector container image.
Push the image to an Azure container registry.
Distribute a docker run script.
Run the container in the local or on-prem environment.
Microsoft References
Use Cognitive Services containers
Azure Container Registry - Authentication and RBAC
Best practices for running Cognitive Services containers
